Public Health, Ph.D. - Health Services and Policy Research Concentration

The following Ph.D. Health Services and Policy Research (HSRP) competencies describe the knowledge, skills, and abilities a successful graduate will demonstrate the conclusion of this doctoral program (and the course where the competency is mastered and assessed is noted in parenthesis):

Ph.D. HSRP 1: Apply social science (economics, political science, sociology, etc.) concepts, theories and methods to the framing and analysis of research questions in health services delivery and health care policy. (PHPB 9240 )
Ph.D. HSRP 2: Describe major problems in health services delivery and health care policy that are currently the subject of empirical investigations. (PHPB 9220 )
Ph.D. HSRP 3: Apply advanced methods of analysis and research design to describe policy-relevant issues in contemporary health care, such as: access to health care, health care financing, insurance market functioning, physician and hospital performance, healthcare management and organization, patient safety and quality of care, and health care workforce. (PHPB 9240 )
Ph.D. HSRP 4: Effectively teach concepts and methods of health services and health policy research to students. (PHPB 9240 )
Ph.D. HSRP 5: Design a health services or health policy research proposal involving qualitative, quantitative, or mixed methods approaches. (PHPB 9220 )
Ph.D. HSRP 6: Conduct a health services or health policy research activity investigation suitable for peer-reviewed publication as an independent researcher. (PHPB 8250 )
Ph.D. HSRP 7: Function as a collaborative team member in the design and conduct of a health services or health policy investigation. (PHPB 8250 )

Required Ph.D. HSRP Concentration Courses (9 Hours)

PHPB 9220 - Principles of Health Services Research I: Themes 3 Credit Hours
PHPB 9240 - Principles of Health Services Research II: Methods 3 Credit Hours
PHPB 8250 - Health Economics and Policy 3 Credit Hours

Ph.D. HSRP Concentration Advanced Research Methods, Statistics and Electives Courses (18 Hours)

Select at least 6 pre-approved courses in consultation with the Faculty Advisor.

PHPH 8260 - Spatial Population Health I 3 Credit Hours
PHPB 8285 - Social Determinants of Health 3 Credit Hours
PHPB 8290 - Population Health Informatics 3 Credit Hours
PHPH 8330 - Maternal and Child Health Epidemiology: Using Information and Data Systems 3 Credit Hours
PHPB 8331 - Implementation and Scale-Up of Evidence-based Practices for Maternal and Child Health Populations 3 Credit Hours
PHPB 8332 - Maternal and Child Health Advocacy: From Rights to Justice 3 Credit Hours
PHPH 8830 - Advanced Statistical Topics 3 Credit Hours
PHPH 8840 - Statistical Modeling with Latent Variables I: Structural Equation Modeling 3 Credit Hours
PHPH 8850 - Statistical Modeling with Latent Variables II: Finite Mixture Modeling 3 Credit Hours
PHPH 8860 - Multilevel Models in Public Health 3 Credit Hours
PHPH 8885 - Fundamentals of Clinical Trials 3 Credit Hours
PHPH 8890 - Special Topics in Biostatistics 1 to 6 Credit Hours
PHPH 9890 - Doctoral Seminar in Advanced Statistical Modeling 3 Credit Hours
ECON 8220 - Human Resources and Labor Markets 3 Credit Hours
PMAP 8141 - Microeconomics for Public Policy 3 Credit Hours
PMAP 9211 - Applying Research to Policymaking: Examples from Health Care Policy 3 Credit Hours
SOCI 8118 - Aging, Health, and Disability 3 Credit Hours
SOCI 8234 - Race-Ethnicity and Health 3 Credit Hours
Other appropriate Ph.D. HSRP research methods/statistics and elective courses may be approved by the Faculty Advisor on the Doctoral Program of Study form. There are a number of departments at the university that offer relevant courses including, but not limited to, Mathematics and Statistics, Managerial Sciences (Decision Sciences unit), Economics, Marketing, Sociology, Public Management and Policy Studies, Psychology, and Educational Policy Studies (Research unit). Other courses that may be approved to satisfy this elective requirement include, but are not limited to, Structural Equation Modeling, Finite Mixture Modeling, Hierarchical Linear Modeling, Longitudinal Modeling, Survival Analysis, Bayesian Inference, Survey Sampling, Causal Inference, Missing Data, or Nonparametric Statistics. Students are recommended to receive approval from their Faculty Advisor prior to enrolling in, paying for, and completing the course.